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Article . 2024 . Peer-reviewed
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Other literature type . 2024
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Research . 2024
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Computer Science for All? The Impact of High School Computer Science Courses on College Majors and Earnings

Authors: Liu, Jing; Conrad, Cameron; Blazar, David;

Computer Science for All? The Impact of High School Computer Science Courses on College Majors and Earnings

Abstract

This study provides the first causal analysis of the impact of expanding Computer Science (CS) education in U.S. K-12 schools on students' choice of college major and early career outcomes. Utilizing rich longitudinal data from Maryland, we exploit variation from the staggered rollout of CS course offerings across high schools. Our findings suggest that taking a CS course increases students' likelihood of declaring a CS major by 10 percentage points and receiving a CS BA degree by 5 percentage points. Additionally, access to CS coursework raises students' likelihood of being employed and early career earnings. Notably, students who are female, low socioeconomic status, or Black experience larger benefits in terms of CS degree attainment and earnings. However, the lower take-up rates of these groups in CS courses highlight a pressing need for targeted efforts to enhance their participation as policymakers continue to expand CS curricula in K-12 education.

Keywords

high school curricula, ddc:330, I23, J24, H52, computer science, STEM, college major choice, earnings

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Beta
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